Abstract #M252
Section: Ruminant Nutrition
Session: Ruminant Nutrition I
Format: Poster
Day/Time: Monday 7:30 AM–9:30 AM
Location: Exhibit Hall B
Session: Ruminant Nutrition I
Format: Poster
Day/Time: Monday 7:30 AM–9:30 AM
Location: Exhibit Hall B
# M252
miRNA regulation of the neutrophil transcriptome in response to prepartal energy intake in Holstein cows: an in silico approach.
M. Vailati Riboni*1, V. Palombo2, A. Agrawal1, M. J. Khan1, J. J. Loor1, 1Urbana, IL 61801, Urbana, IL, 2Università degli Studi del Molise, Campobasso, Italy.
Key Words: miRNA, PMNL, transition cow
miRNA regulation of the neutrophil transcriptome in response to prepartal energy intake in Holstein cows: an in silico approach.
M. Vailati Riboni*1, V. Palombo2, A. Agrawal1, M. J. Khan1, J. J. Loor1, 1Urbana, IL 61801, Urbana, IL, 2Università degli Studi del Molise, Campobasso, Italy.
Overfeeding energy prepartum leads to a chronic and potentially detrimental activation of PMNL during the adaptation to lactation. Using microarray transcriptome data, the present study aimed to examine the role of microRNA (miRNA) in the observed expression profiles in response to prepartal energy intake. Sixteen Holstein cows were fed a high-straw, control diet (NEL = 1.34 Mcal/kg) or overfed a moderate-energy diet (NEL = 1.62 Mcal/kg) during the dry period. PMNL were isolated from blood at −14 and +7 d relative to parturition and isolated RNA was hybridized to the Agilent 44K Bovine (V2) Microarray chip. Data were adjusted for dye and array effects and a MIXED model with repeated measures was then fitted to the normalized log2-transformed adjusted ratios. A list of miRNA families and their predicted target genes for Bos taurus were downloaded from the Microcosm targets website (v. 5.0). Results for the main effect of diet were then used to predict miRNA activity from the mRNA expression profiles through 3 approaches: Wilcoxon rank test, ranked ratio, and mean absolute expression. The dynamic impact approach was then used for pathway analysis on the compiled differentially expressed target genes (false discovery rate <0.05) of the predicted miRNA. Overlapping the results of the 3 approaches, 10 miRNA were predicted to be involved in the observed transcriptome changes: miR-let7a, miR-26a, miR-101, miR-126, miR-191, miR-200a, miR-369, miR-374, miR-450, and miR-545. Pathway analysis revealed an overall impact on amino acid, cofactor, and vitamin metabolism, with a particular involvement in the one-carbon metabolism (e.g., methionine, and folate cycle). ‘Translation’, ‘folding, sorting, and degradation’, ‘DNA repair’ and ‘cell growth and death’ were among the most-impacted non-metabolic category, together with immune processes such as the ‘NOD-like receptor’ and ‘Fc episilon RI’ signaling pathways, and ‘Fc gamma R-mediated phagocytosis’. Overall, data support the role of miRNA in the PMNL response to prepartum overfeeding, particularly in non-metabolic processes.
Key Words: miRNA, PMNL, transition cow